Academic literature on the topic 'Fr risk assessment'

Previous wildfire risk assessments have problems such as subjectivity of weight allocation and the linearization of statistical models, resulting in generally low robustness and low generalization ability of fire risk assessment models. Therefore, in this paper, we explored the potential of integration machine learning algorithms to build wildfire risk assessment models. Based on analyzing fire data’s spatial and temporal distribution, we selected 10 triggering factors of topography, meteorology, vegetation, and human activities, using frequency ratio (FR) to provide uniform data representation of triggering factors. Next, we used the Bayesian optimization (BO) algorithm to perform hyperparametric optimization solutions for various machine learning models: support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost). Finally, we constructed an integration machine learning algorithm to acquire a fire risk grading map and the importance evaluation corresponding to each triggering factor. For validation purposes, we selected Liangshan Prefecture in Sichuan Province as the specific study area and obtained MCD64A1 burned area product to extract the extent of burned areas in Liangshan Prefecture from 2011 to 2020. The accuracy, kappa coefficient, and area under curve (AUC) were then applied to assess the predictive power and consistency of the fire risk classification maps. The experimental analysis showed that among the three models, FR-BO-XGBoost had the best performance in wildfire risk assessment in the Liangshan region (AUC = 0.887), followed by FR-BO-RF (AUC = 0.876) and FR-BO-SVM (AUC = 0.820). The feature importance result indicated that the study area’s most significant effects on wildfires were precipitation, NDVI, land cover, and maximum temperature. The proposed method avoided the subjective weighting and model linearization problems. Compared with the previous methods, it automatically acquired the importance of the triggering factors to the wildfire, which had certain advantages in wildfire risk assessment, and was worthy of further promotion.

Abstract Metropolitan governments and water operators are continuously facing the ever-growing challenges of evaluating the risks and optimizing investment in the rehabilitation of the buried aging infrastructure of water distribution systems (WDS). Proper asset management and efficient rehabilitation planning require monitoring, condition assessment, degradation risk analysis and a data-based model for degradation forecasting to support investment decision-making and significantly reduce the infrastructure rehabilitation cost. This paper presents a statistical and stochastic spatial data analysis of failure records of the WDS of the City of Wattrelos, France. The research objective is to develop and demo-illustrate the application of an operator's experience-based Risk Assessment Method (RAM) for network micro-zone prioritization of rehabilitation/replacement works to optimize preemptive asset management. The data used is a 74-year historical dataset from Wattrelos, France. The database includes approximately 424 observed failures for the period of 1991–2004. The data analysis demonstrates that understanding and using stochastic modeling to characterize the pattern of relationship between Failure Rate (FR), Age (T) and the Probability (or Risk) of exceeding a specific Failure Rate (Pr(FR)) of a micro-zone can effectively support the operator's assessment, risk management and prioritization in the maintenance and rehabilitation of the WDS.

Abstract Introduction. Risk factors associated with falling in the elderly are numerous. Most existing tools use a combination of functional assessment and risk scoring based on known risk factors. The aim of the study was to verify which parameters could be used to predict fall risk (FR) in older women. Material and Methods. The study involved 56 inactive females aged 71.77 ± 7.43(SD). Backward stepwise regression analysis was performed to determine which independent variables predict FR in older women. Results. Significant predictors of FR were: in model 1 – age and body mass (in 32%); in model 2 – knee extensor strength of the right lower limb (KEs R) (in 20%); in model 3 – the Timed up and Go test (TUG) (in 25.5%); and in model 4 – medial-lateral stability index with eyes open (MLSI EO) (in 35%). By means of backward stepwise regression analysis using the above models, the variables that significantly influence FR in seniors were body mass, MLSI EO, KEs, and age. The above analysis shows that these indicators (model 5) may predict FR in older women in 59% of cases. Conclusions. It was determined that variables that significantly influence FR in seniors were body mass, age, KEs, and MLSI EO. Research should be continued to identify more predictors and define norms that indicate FR.

Introduction. Falls among the elderly are an important community health problem due to its high incidence, functional and social repercussion. Dissimilar results arose in recent studies concerning fall risk and physical activity levels. This study measures the association between physical activity (PA) levels, and fall risk (FR), investigates which levels of PA are influential in FR and presents a fall risk prediction models for the elderly. Material and Methods. One hundred and seventy elderly adults (72.34 ± 6.70 years old, 124 female), completed Performance-Orientated-Mobility-Assessment; PA was assessed by accelerometry. Pearson’s correlation verified the association between FR, Age, and PA. Multiple linear regression (MLR) was used to investigate the influence of variables on FR. Results. PA, age are predictors of FR, with PA (moderate, negative) age (moderate, positive). MLR analysis showed FR variability explained by PA (42.0%) and by age (37.0%), and by gender, female FR explained by light PA (47.0%), while in male, FR explained by sedentary behaviour (44.1%) and age (22.7%) independently. Conclusion. Individuals with higher physical activity have lower fall risk. Older are prone to fall. Older women with light physical activity are less likely to fall. Older men with more sedentary behaviour are prone to fall.

Food reactions (FR) are multifactorial and impacted by medical, demographic, environmental, and immunologic factors. We hypothesized that multi-omic analyses of host-microbial factors in saliva would enhance our understanding of FR development. This longitudinal cohort study included 164 infants followed from birth through two years. The infants were identified as FR (n = 34) or non-FR (n = 130) using the Infant Feeding Practice II survey and medical record confirmation. Saliva was collected at six months for the multi-omic assessment of cytokines, mRNAs, microRNAs, and the microbiome/virome. The levels of one miRNA (miR-203b-3p, adj. p = 0.043, V = 2913) and one viral phage (Proteus virus PM135, adj. p = 0.027, V = 2955) were lower among infants that developed FRs. The levels of one bacterial phylum (Cyanobacteria, adj. p = 0.048, V = 1515) were higher among infants that developed FR. Logistical regression models revealed that the addition of multi-omic features (miR-203b-3p, Cyanobacteria, and Proteus virus PM135) improved predictiveness for future FRs in infants (p = 0.005, X2 = 12.9), predicting FRs with 72% accuracy (AUC = 0.81, sensitivity = 72%, specificity = 72%). The multi-omic analysis of saliva may enhance the accurate identification of infants at risk of FRs and provide insights into the host/microbiome interactions that predispose certain infants to FRs.

Background and Aim. This study is aimed at comparing the Functional Reach Test (FRT), Timed Up and Go (TUG), and a modified Unterberger test with stabilographic parameters (Biodex Balance System—BBS), to assess fall risk (FR) in older women. Methods. Fifty-five females were examined (May 2018-June 2019). Stabilographic examinations were performed with eyes open (EO) and closed (EC). An analysis of variance (ANOVA) and Spearman rank correlation were performed to determine the relationships and differences between the above tests. Results. The results of the TUG correlate with the overall stability index (OSI) EO ( r = 0.314 ), medial-lateral stability index (MLSI) EO ( r = 0.297 ), and fall risk index (FRI6-2; r = 0.435 ) in stabilographic examinations and the FRT ( r = − 0.399 ). The results of the modified Unterberger test correlate with MLSI EO ( r = 0.276 ), OSI EC ( r = 0.310 ), and MLSI EC ( r = 0.378 ). There are statistically significant differences between faller and nonfaller groups in TUG ( p = 0.0068 ), FRT ( p = 0.001 ), and MLSI EO ( p = 0.0118 ). Conclusions. The modified Unterberger test and TUG can be considered effective in functional FR assessment in older women. Using at least two different functional tests may improve the assessment of FR.

Steady-state operations are used globally in chemical engineering. Advantages include ease of control and a more uniform product quality (Ghasem and Henda, 2008; McCabe et al, 2001). Importantly however, there will be naturally occurring, random (stochastic) fluctuations in parameter values about the ‘set’ mean when process control is inadequate. These are not addressed explicitly in traditional chemical engineering because they are not sufficient on their own to be considered transient (unsteady) and because, generally, fluctuations in one parameter are off-set by changes in others with plant output behaviour seeming to remain steady (Amundson et al., 1980; Sinnott, 2005; Zou and Davey, 2016). Davey and co-workers, however, have demonstrated these fluctuations can unexpectedly accumulate in one direction and leverage significant (sudden and surprise) change in output behaviour with failure in product or plant (e.g. Abdul-Halim and Davey, 2016; Zou and Davey, 2016; Chandrakash and Davey, 2017). To underscore the unexpected element of the failure event they titled their risk framework Fr 13 2 (Friday 13th Syndrome). Case studies of their probabilistic risk framework to 1-step operations include loss of thermal efficiency in a coal-fired boiler (Davey, 2015 a) and failure to remove whey deposits in Clean-In-Place (CIP) milk processing (Davey et al., 2015). More recently, to advance their risk framework for progressively, multi-step and complex (in the sense of ‘integrated’, not ‘complicated’) processes they demonstrated its usefulness to 2-step membrane fouling with combined ultrafiltration-osmotic distillation (UF-OD) (Zou and Davey, 2016), and; a 3-step microbiological raw milk pasteurization (Chandrakash and Davey, 2017). Findings overall revealed no methodological complications in application - and it was concluded the risk framework was generalizable (Zou and Davey, 2016; Chandrakash and Davey, 2017). A significant advantage of the framework is it can be used in ‘second-tier studies’ to reduce risk through simulations of intervention strategies and re-design of physical plant or operating practice. It can be applied at both synthesis and analysis stages. 2 see Appendix A for a definition of some important terms used in this research. Although the risk framework has been successfully applied to corrosive pitting of AISI 316L metal widely used in off-shore oil and gas structures (Davey et al., 2016) 3 it was not known if it could provide new insight into corrosion of metal, more specifically microbiologically influenced corrosion (MIC), a major problem globally that accounts for ~ 20 % of overall corrosion (Flemming, 1996). It is estimated to cost AUD$7 billion to Australia annually (Javaherdashti and Raman-Singh, 2001). A review of the literature showed that a thorough understanding of MIC has been slow to emerge, both because of the role of micro-organisms in corrosion and because of a lack of methodology to determine any impact of natural fluctuations in the internal pipe environment. Importantly, the insidious nature of MIC was known to pose a practical risk of failure of pipes used to transport wet-fluids. However, because modelling of direct MIC would be uniquely complex it was planned that a general model for corrosion should be synthesized and understood that could be extended. A limited research program was therefore undertaken with the aim to advance the Fr 13 framework and to gain unique insight into how naturally occurring fluctuations in fluid temperature (T) and pH of the internal pipe environment can be transmitted and impact corrosion. A logical and stepwise approach was implemented as a research strategy. The initial model of Smith et al. (2011) was modified to simulate MIC causing micro-organisms such as sulphate-reducing bacteria (SRB) on widely used ASTM A105 carbon-steel pipe that is corroded under steady-state, abiotic and synthetic conditions. This was solved using traditional, deterministic simulations to give a predicted, underlying corrosion rate (CR) of 0.5 mm yr-1 as impacted by internal pipe-fluid T and pH. Importantly, findings underscored the controlling importance of low pH on CR. This initial model was then simulated, for the first time, using the probabilistic Fr 13 framework (Collins et al., 2016) 4 in which distributions to mimic fluctuations in T (K) and 3 This research was a Finalist, IChemE Global Awards 2016, Innovative Product, Manchester, UK, Nov. 4 Collins, S.D., Davey, K.R., Chu, J.Y.G., O’Neill, B.K., 2016. A new quantitative risk assessment of Microbiologically Influenced Corrosion (MIC) of carbon steel pipes used in chemical engineering. In: pH in the pipe were (reasonably) assumed as truncated Normal, and; a new corrosion risk factor (p) was synthesized such that all p > 0 characterized a CR failure i.e. a corrosion rate greater than 0.5 mm yr-1. Normal distributions that were truncated were used because these permitted T and pH to fluctuate randomly during process operations but limited these to values that could occur only practically. Predictions showed that 28.1 % of all corrosion of ASTM A105 pipe, averaged over the long term for a range of fluctuations 290.15 ≤ T ≤ 298.15 K, and 4.64 ≤ pH ≤ 5.67, would in fact be greater than the underlying value despite a design margin of safety (tolerance) of 50 % CR, and were therefore process failures (p > 0). Findings highlighted that corrosion was a combination of ‘successful’ and ‘failed’ operations. This insight is not available from traditional risk approaches, with or without sensitivity analyses. It was concluded that the Fr 13 framework was an advance over the traditional, deterministic methods because all corrosion scenarios that can practically exist are simulated. It was concluded also that if each simulation was (reasonably) thought of as one operational day, there would be (28.1/100 days × 365.25 days / year) ~103 corrosion failures in ASTM A105 pipe per year. However it was acknowledged that to enhance corrosion simulation, the free corrosion potential (Ecorr, V vs SCE), a key parameter in this initial model formulation, should more realistically be considered a combined function of the internal pipe-fluid T and pH, and; that this assumption should be tested, and, that this would necessitate a trial-and-error simulation for corrosion rate (CR). It was also determined that the truncations that were used for T and pH were too restrictive for off-shore oil processing (Arnold and Stewart, 1999; J. Y. G. Chu, Upstream Production Services Pty Ltd., Australia, pers. comm.). To address this, the initial model was extended mathematically for the first time, and; Fr 13 risk simulations carried out using spread-sheeting techniques utilizing the Solver CHEMECA 2016: Chemical Engineering – Regeneration, Recovery and Reinvention, Sept. 25-28, Adelaide, Australia, paper 3386601. ISBN: 9781922107831 function (Microsoft Excel™). A significant advantage was that the distributions defining the naturally occurring fluctuations in T and pH could be entered, viewed, copied, pasted and manipulated as Excel formulae. Predictions showed (Collins and Davey, 2018) 5 an underlying corrosion rate CR = 0.45 mm yr-1 – a change of approximately 10 % when the design margin of safety (tolerance) was reduced from 50 % to a more realistic 20 % for the improved model. This is significant because the tolerance of a model should be as low as can be accepted, as higher tolerances can infer that the process is safer than it actually is. Fr 13 simulations showed that 43.6 % of all corrosion of internal ASTM A105 pipe, averaged over the long term for a range of realistic fluctuations 282.55 ≤ T ≤ 423.75 K, and 4.12 ≤ pH ≤ 6.18 would be deemed to be process pipe-failures (p > 0). This translates to a corrosion failure in ASTM A105 pipe every 160 days, averaged over the long term. It is not expected that these would be equally spaced however. Findings were used in investigative ‘second-tier’ studies to explore possible intervention strategies to reduce vulnerability to corrosion and to improve plant design and safety. For example, repeat Fr 13 simulations revealed that, for a fixed mean-value of T = 353.15 K a decrease in pH from 5.15 to 4.5 resulted in an increase in carbon-steel pipe corrosion of ~1.55 mm yr-1 i.e. ~347 % increase. This implied that the pipe vulnerability to Fr 13 corrosion failure could be practically minimised by adding bases, such as potassium hydroxide or sodium carbonate (Kemmer, 1988). However, if the pH is too high, anions in the pipe-fluid could precipitate and form insoluble mineral scales, leading to fouling (Pichtel, 2016). It is acknowledged that the present research is limited to an abiotic system i.e. one without micro-organism kinetics. A justification is that the models presented in this research should be seen as a ‘starting point’, which could be expanded in later iterations to include: biotic model components such as the simple bacterial kinetics in the predictive MIC model of Maxwell and Campbell (2006); other species that are involved in MIC such 5 Collins, S.D., Davey, K.R., 2018. A novel Fr 13 risk assessment of corrosion of carbon-steel pipe in de-aerated water. Chemical Engineering Science – submitted CES-D-18-00449, Feb. as sulphates, chlorides and hydrogen sulphide (H2S); different metals/alloys that are used in pipe equipment where MIC can be found e.g. copper or zinc (Roberge, 2000), or; a ‘global’ model i.e. two or more connected unit-operations (Chandrakash and Davey, 2017). (A global model however, might not be applicable because MIC can be initiated in localized sites (Roberge, 2000)). It is concluded that these thesis findings nevertheless significantly enhance understanding of factors that lead to excessive corrosion rates in ASTM A105 pipes. It is concluded also that the Fr 13 risk framework appears generalizable to a range of micro-organism-metal systems and is an advancement over current existing risk and hazard assessments. If properly developed, it is thought that this risk technique could be adopted as a new design tool for steady-state unit-operations in both the design and synthesis stages and to increase understanding of MIC behaviour and outcomes. This research is original and not incremental work. Results and findings will be of immediate benefit and interest to a range of risk analysts, and to a broad range of practical operations involving carbon-steel pipe flows
Thesis (MPhil) -- University of Adelaide, School of Chemical Engineering & Advanced Materials, 2018

Steady-state unit-operations are used globally in chemical engineering processing. Importantly however, there are naturally occurring (random) fluctuations in parameter values about a ‘set’ mean. These are not sufficient to be considered transient and a random change in one is often off-set by a change in another - with the result that the output remains seemingly steady. Significantly, traditional chemical engineering does not address these random fluctuations explicitly. Davey and co-workers (e.g. Abdul Halim and Davey, 2015; Zou and Davey, 2016) have shown that these natural fluctuations can combine and accumulate in one direction and leverage unexpected and surprise behaviour across a ‘failure - not failure’ boundary. Their hypothesis they titled Fr 13 (Friday 13th) to underscore the surprise element of the failure event. Their probabilistic Fr 13 framework has been usefully applied to a number of 1-step unit-operations including failure in: UV irradiation for potable water (Abdul-Halim and Davey, 2015; 2016); thermal efficiency of a commercial coal-fired boiler (Davey, 2015), metals pitting (Davey et al., 2016), and; failure to remove whey protein deposits in Clean-In-Place milk processing (Davey et al., 2015). A significant advantage is that the framework can be used in quantitative ‘second-tier’ studies (Abdul-Halim and Davey, 2016) to improve design and safety of unit-operations. A limitation however is that the framework had been applied to only 1-step (single) unit-operations until very recently when Zou and Davey (2016) demonstrated its applicability to integrated 2-step membranes processing. Generally however, it is not known if there is any benefit in developing the framework as a useful tool for integrated, greater multi-step unit-operations and its possible combination (Davey et al., 2013) with existing software to enhance design capability. Davey (2011) had suggested these integrated multi-step analyses be termed ‘global’ models. A research program is therefore undertaken with the aim to advance the Fr 13 framework to gain unique insight into how naturally occurring fluctuations in apparent steady-state plant parameters can be transmitted and impact in progressively complex (in the context of ‘integrated’ not ‘complicated’) multi-step processes, and to assess the framework as a new design tool. A logical and stepwise approach is implemented as a research strategy. Because foods processing is globally the largest manufacturing sector, and within it, pasteurization is the most widely used unit-operation, a typical 3-step pasteurization unit operation, consisting of individual 1) heat-up, 2) holding and 3) cool-down, unit-operations is selected as a prudent and stringent test of the Fr 13 risk thesis to multi-step unit-operations. An initial assessment, based on typical commercial pasteurization equipment for raw milk (plate heat exchangers and an external-coil holding tube) is synthesized for the first time (Chandrakash et al., 2015; 2014; Davey et al., 2014) and a generalized method of notation for the Fr 13 risk framework is developed to unambiguously identify particular unit-operations in integrated multi-step processes. Failure is defined in terms of not meeting a globally used Regulatory combination of temperature (T) - time (t) (72 °C, 15 s). Results revealed that pasteurization of raw milk is vulnerable to failure in 12.5 % of all cases over the long-term as a result of with-in system fluctuations in flows, and thermal conditions. If each simulation is (reasonably) considered a daily process this translated to some 46 failures each year with a 2 % design tolerance 2 to meet the required T - t pasteurization criteria. Results highlighted that apparent steady-state pasteurization is actually a combination of successful and (potential) failed operations. This insight could not be obtained from existing traditional risk and hazard approaches, with or without sensitivity analyses. A drawback soon acknowledged however, is that this equipment model did not explicitly address the reduction in unwanted levels of survival of potential contaminant microorganisms in the treated milk. To overcome this, a microbiological global risk model is developed for the first time for the 3-step pasteurization. The logarithmic reduction of viable Mycobacterium avium subsp. paratuberculosis (MAP), a common bacterial contaminant and pathogen, is selected as an indicator of efficacy of process, and an inactivation model is then synthesized (Chandrakash and Davey, 2017 a). Results showed that for a design Regulatory reduction of log₁₀ = 5.5 in viable MAP the 3-step pasteurization is vulnerable to failure in 5.75 % of cases with a 2 % design tolerance averaged over the long term. This equated to ~ 21 failures with viable MAP each year based on a daily operation. To further test applicability of the risk framework to multi-step processing, a fourth integrated step, the storage of the pasteurized milk, is added for the first time (Chandrakash and Davey, 2017 b). A justification is that this simulated commercial practice more closely. Results of simulation of this 4-step model showed that with a design tolerance of 2 % for a Regulatory design reduction of log₁₀ = 5.5 in viable MAP on heat-up to 72 °C with 15 s holding in commercial plate equipment, there would be no further failures i.e. the rate of vulnerability to failure in a 4-step microbiological model for pasteurizing and storing milk remained 5.75 %, averaged over the long term. Results from investigative second-tier studies with the new 4-step Fr 13 model to improve design and safety, revealed vulnerability to microbiological failure can be readily mitigated by installing precise safety-integrity-level (SIL) mass flow control on the raw milk in existing plant to ensure a holding time of ≥ 15 s. It is concluded the Fr 13 framework appears generalizable to integrated multi-step steady-state processes without methodological problems and an advance over current existing risk/hazard methodologies. If properly developed, it is believed that this novel framework could be adopted as a new design tool for steady-state processing at both design and synthesis stages. Research findings will aid a detailed understanding of factors that contribute to failures, and to increased confidence in steady-state unit-operations processing. This research work is original and not incremental work. Findings will be of direct interest to risk analysts, milk processors and manufacturers of pasteurizer equipment.
Thesis (Ph.D.) -- University of Adelaide, School of Chemical Engineering, 2017.

Soldiers, first responders and other high risk occupations such as power line technicians are routinely exposed to dangerous situations where severe burn injuries are possible. Standard flame resistant (FR) fabrics provide minimal burn protection when exposed to a flash flame incident. As a result, improvement in thermal protection is desperately needed and remains an ongoing subject of research and development. A simplified one dimensional physical model composed of a muscle layer, skin/fat layer, air gap(s) and fabric layer(s) is used to model heat transfer entering the body covered by a garment that is exposed to a flash flame. Heat transfer within the skin and muscle layers is modeled by combined conduction, metabolic heat generation and blood perfusion by a recently developed modification to the heat equation termed the bio-heat equation. Boundary conditions include a fixed temperature (core body temperature) at the inside of the muscle layer and combined convection and radiation from the flame on the outside of the fabric. The heat equation is solved by discretizing the domain in one dimension and using a finite volume approach to derive the finite difference equations. This model is an initial step to be used to provide an assessment of common FR garments with respect to both comfort in ambient conditions and protection during a flash flame. It also provides for parametric analysis to determine ideal thermo-physical properties, fabric thicknesses and layering for better protection during flash flame incidents. Estimates for time to burn injury from the numerical model is presented with experimental results using live mannequin flame tests (ASTMF-1930), standard vertical flame tests (ISO-17492) and a non-standard flame test with combined convection and radiation heat fluxes up to 85 kW/m2. The main effort of this study revolves around an initial working design for a dynamic garment termed On Demand Thermal Protection (ODTP). The primary focus of the design is the development of a thermistor circuit embedded in a protective garment to act as an electric sensor for rapidly deploying the necessary thermal protection that is needed as predicted by the numerical model instantaneously in the event of a flash flame incident. An initial prototype is being developed with a focus on designing the thermistor circuit to mechanically actuate protective components in a flash-flame environment. Concepts include rapidly releasing a pressurized flame retardant fluid through vinyl tubing sewn into a garment and deploying a protective barrier around the face and neck when the thermistor circuit detects a sudden change in heat transfer. A summary of the prototype along with experimental testing to date compared to the theoretical predictions from the model described above is presented.